| 1. |
- Jiang, Bin, et al.
(author)
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Location-based services and GIS in perspective
- 2006
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In: Computers, Environment and Urban Systems. - : Elsevier BV. - 0198-9715 .- 1873-7587. ; 30:6, s. 712-725
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Journal article (peer-reviewed)abstract
- This paper examines location-based services (LBS) from a broad perspective involving deWnitions, characteristics, and application prospects. We present an overview of LBS modeling regarding users, locations, contexts and data. The LBS modeling endeavors are cross-examined with a research agenda of geographic information science. Some core research themes are brieXy speculated.
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| 2. |
- Lucas, Carlos, et al.
(author)
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Mathematical model of biomass gasification using high temperature air in fixed beds
- 2007
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In: Progress in Computational Fluid Dynamics, An International Journal. - 1468-4349 .- 1741-5233. ; 7:1, s. 58-67
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Journal article (peer-reviewed)abstract
- A mathematical model has been formulated for predicting the main chemical and physical processes taking place during the fixed-bed gasification of biomass fuels using high temperature air (up to 1000 degrees C). Predicted gas species concentrations profiles and their maximum values are in good agreement with measurements. The results also show that when the temperature of feed gas (air) is increased a higher gasification rate, higher molar fractions of fuel gases (CO, H-2 and CmHn) are obtained, thus resulting in a higher LHV. At a high flow rate of the feed gases, the peaks of the fuel gas concentrations are slightly increased, and the gasification rate is strongly increased. A smaller particle size of the biomass fuels leads to higher peak values of the fuel gas species molar fractions, and a more stable gasification zone for a relatively long period of time.
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| 3. |
- Xie, Yao, et al.
(author)
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Multistatic adaptive microwave imaging for early breast cancer detection
- 2006
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In: IEEE Transactions on Biomedical Engineering. - 0018-9294 .- 1558-2531. ; 53:8, s. 1647-1657
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Journal article (peer-reviewed)abstract
- We propose a new multistatic adaptive microwave imaging (MAMI) method for early breast cancer detection. MAMI is a two-stage robust Capon beamforming (RCB) based image formation algorithm. MAMI exhibits higher resolution, lower sidelobes, and better noise and interference rejection capabilities than the existing approaches. The effectiveness of using MAMI for breast cancer detection is demonstrated via a simulated 3-D breast model and several numerical examples.
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| 4. |
- Xie, Yao, et al.
(author)
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Novel multistatic adaptive microwave imaging methods for early breast cancer detection
- 2006
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In: Eurasip Journal on Applied Signal Processing. - 1110-8657. ; , s. 91961-
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Journal article (peer-reviewed)abstract
- Multistatic adaptive microwave imaging (MAMI) methods are presented and compared for early breast cancer detection. Due to the significant contrast between the dielectric properties of normal and malignant breast tissues, developing microwave imaging techniques for early breast cancer detection has attracted much interest lately. MAMI is one of the microwave imaging modalities and employs multiple antennas that take turns to transmit ultra-wideband (UWB) pulses while all antennas are used to receive the reflected signals. MAMI can be considered as a special case of the multi-input multi-output (MIMO) radar with the multiple transmitted waveforms being either UWB pulses or zeros. Since the UWB pulses transmitted by different antennas are displaced in time, the multiple transmitted waveforms are orthogonal to each other. The challenge to microwave imaging is to improve resolution and suppress strong interferences caused by the breast skin, nipple, and so forth. The MAMI methods we investigate herein utilize the data-adaptive robust Capon beamformer (RCB) to achieve high resolution and interference suppression. We will demonstrate the effectiveness of our proposed methods for breast cancer detection via numerical examples with data simulated using the finite-difference time-domain method based on a 3D realistic breast model.
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| 5. |
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| 6. |
- Yao, Xiaobai, et al.
(author)
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Geospatial modeling of urban environments
- 2009
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In: Environment and Planning, B. - : SAGE Publications. - 0265-8135 .- 1472-3417. ; 36:5, s. 769-771
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Journal article (other academic/artistic)
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